Ronald Mutegeki
Field Application Engineer
Seoul, South Korea
Summary
👤
Senior🎓
Top SchoolRonald Mutegeki is a Field Application Engineer based in Seoul with nine years of experience building and deploying robotics, simulation, and AI-driven software for automotive and smart-factory domains. He pairs hands-on expertise in Deep Reinforcement Learning, ROS2, PyBullet/Gazebo simulation, and embedded perception (IMU, camera, LiDAR) with a customer-focused approach to accelerate product development using dSPACE platforms. Previously a Software Engineering Manager, he led teams to create Maicat (a reinforcement-learning powered robotic cat integrated with smart homes) and Maidynamics for digital-twinning and factory automation. His background spans full-stack and embedded development across Python, C++, mobile frameworks, cloud deployments, and ML research—highlighted by a 3.75 MS in Computer Science and a practical HAR dataset and model from his academic work. Known for translating research into deployable systems, he aims to blend leadership and technical depth to bring autonomous solutions to market.
9 years of coding experience
8 years of employment as a software developer
Master's degree, Computer Science, 3.75, Master's degree, Computer Science, 3.75 at Kyungpook National UniversityFullstack Software Engineering Program, Computer Software Engineering, Fullstack Software Engineering Program, Computer Software Engineering at Holberton SchoolLanguage Course, Korean Language and Literature, Level 4, Language Course, Korean Language and Literature, Level 4 at Inha UniversityBachelor of Science (B.Sc.), Computer Science, 4.15, Bachelor of Science (B.Sc.), Computer Science, 4.15 at Makerere University
English, Korean, Swahili, Bantu, runyakitara
Stackoverflow
1reputation
0reached
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Github Skills (19)
sensor10
modulation9
predict9
imu9
terrain9
prediction9
pybullet8
bezier8
openai-gym8
ignition8
dynamics7
ros7
optimization7
machine-learning6
python6
Programming languages (2)
Github contributions (5)
rmutegeki/alx-higher_level_programming
Sep 2022 - Jun 2023
Contributions:369 pushes, 1 branch in 8 months
rmutegeki/iSPL-CESLeA
Oct 2019 - Feb 2021
This is a repository for ISPL's turnkey project on Behavioral Prediction (인식예측). We use IMU sensor data collected from standalone sensor devices, smartphones, smartwatches and other on-body gadgets to learn a user's behavior and predict their patterns.
Contributions:72 commits, 57 pushes, 7 branches in 1 year 3 months
gadgetspythonturnkeypredictimu-sensor
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